Risk analysis is an integral part of any decision we make. We
constantly face uncertainty, ambiguity and variability around us. Even in spite
of unprecedentedly wide access to information, we cannot precisely predict
future and our project development.

Our experience in project managing and providing consultation services in
Ukraine and Russia strongly shows that relatively insignificant part of
companies performs risk analysis and further explanation of how the projects
should be manages in the context of changes.

Most of companies, especially small, prefer act using rabbit hole logics. Do
you remember, Alice in Wonderland fell into rabbit hole and has been falling,
all things and events were sweeping by her and she was doing nothing, but
passively observing.

Nevertheless, it is good to remember that project success constituent (and
any beginning) is definitely in risk management, “it is necessary to manage
risks professionally. Expert never loses in any way, even in the worst rate, and
if the deal is successful, the expert takes to the maximum.” (from Preferans
Guide)

Within risk management, there exist both qualitative and quantitative
analytical methods. However, when it comes to “roulette risks” – all around the
world may be heard words – Monte Carlo, recollecting statistical modeling method.
For the first time this method was used by scientists who were designing a
nuclear bomb; it was named after Monte Carlo – resort in Monaco, famous for its
casinos and gambling industry.

In this article we will study Monte-Carlo method and its realization in
Spider Project program complex.

Within Monte Carlo method risk analysis is performed by applying possible
results models. When creating such models any factor pertained to be uncertain
is changed by value range, moreover, every time other random value set of
probability function is used. Monte Carlo simulation permits to receive
distribution of values for potential consequences.

In Spider Project the value range, necessary for calculation, is
designated by direction of optimistic, expected and pessimistic parameter
estimation (duration and operation volumes, labor input, productivity, quantity
and resources loading, operation and resources calendars, required expenses and
materials consumption) which are common to be uncertain. (see fig. 1).

Main point of this method consists in performing range of simulations:

program imitates “a throw of dice” and generates in a random way values
selection, which may be possible values of duration of each task in which
different values are possible;

duration of each task is selected, critical path and also general
duration and project completion date are calculated. (In Â Spider Project
there exists a concept “critical index” – percentage ratio of entering the
task on critical path (see fig. 3));

Figure 3. Critical index

as a result, simulation range for each task and project there
shall be specified duration and completion date which «is drawn» more
often, and so its more likely value is assessed;

as a result we get distribution of probabilities for project possible
duration and completion date (see fig.4).

Figure 4. Distribution of probabilities for possible
project duration

Figure 5. Distribution of probabilities for possible
project price

It goes without saying that using of such method shows pinpoint accuracy by
more number of simulations. From time to time for modeling accomplishment, it is
necessary to perform thousands and dozens of thousands of recalculations.

Method of Monte Carlo simulation is more comprehensive idea of possible
events. It helps to assess not only what may happen but also the probability
of such result.

Modeling by Monte Carlo Method has the range of advantages in comparison with
deterministic or “point estimation” analysis.

Probabilistic results. Results demonstrate both possible events
and probability of their occurrence.

Graphical representation of results. Nature of data received when
applying Monte Carlo method permits create graphics of different
consequences and probability of their occurrence. It is important when
transferring the results to interested parties.

Sensitivity analysis. With few exceptions, deterministic analysis
impedes determination which of variables influences to the maximum extent
the results. When Monte Carlo simulation you may see what initial data makes
the most impact on ultimate results

Script analysis. It is very complicate in deterministic models
simulate various values combinations for various initial values, and,
consequently, to assess influence of really dissimilar scripts. Applying
Monte Carlomethod analysts may precisely define what initial data leads to
certain values, and trace the occurrence of specific consequences. It is
very important for performing further analysis.

This method is applied by professionals in different spheres, in particular:
finance, project management, oil and gas industry, transport and environmental
protection.

Monte Carlo simulation helps to study all possible consequences of your
decisions and assess risk influence on project goals (terms, price, etc.), which
provides higher effectiveness in decision making in conditions of ambiguity.

In the next article, there will be introduced Step-by-Step Guide to Risk
Analysis in Spider Project Software Using Monte Carlo Simulation.

Particularly I would like to mention positive style of information used by lecturer. Thank You!”

Irina Pantel

Project Manager,
ALEKS

Two days passed very fast! Respect to consultants :) Topic was clearly described, interesting material, good mastering of audience attention”

Igor Lutsenko

Manager of IÑC Department,
DTEK

It was very interesting; everything was clearly explained, practical tasks helped to apply theoretical knowledge to my projects”

Maria Beketova

Manager of Project Department,
APT-DNEPR

The course has completely proved my expectations, good quality of handling the material”

Konstantin Naumenko

Engineer,
MTS

The seminar was introduced in logical order which helps step-by-step to probe deep into the basic knowledge in “Project management. In general I’m satisfied with seminar and solidified previous knowledge.”

Yelizaveta Balyuk

Project Manager Assistant,
BANKOMSVYAZ

Very intelligent and interesting statement of material, a number of questions have been cleared up”

Andrey Storchevoi

Manager of software applications Department,
Ibox

Everything was laconically, clear and just excellent”

Aleksey Mikhailov

Chief Specialist,
DTEK

Very useful course which gives a great opportunity to train and assess your knowledge. Thank You all”

Aleksandra Udovenko

Service Administrator,

Well disclosed such a complicated topic, proficiently given examples, all information was easy to understand, all questions I was interested in were answered”

Nataliya Nazar

Project Management Expert,
PRYKARPATTIAOBLENERGO, PJSC

I’m very satisfied with the practical course. All hot questions concerning Project and Team management are disclosed”

Denis Dobryvecher

Manager of Designing Group,
BANKOMSVYAZ

Informative seminar, good organization”

Aleksey Saprykin

Project Manager,
EINDMILLS CONSULT

The seminar has brought dozens of positive emotions, highlighted key points on the specific moments that will be helpful in my work with projects. Wonderful impression from lecturers, who clearly and distinctly set the material”

Anna Kokorina

Analyst of consolidated information,
SEVASTOPOLGAS PJSC

I liked the seminar. I obtained interesting information which will help me in my work”

Received positive effect from the structuring of knowledge gained, assessment and setting priorities of all my existing projects + reflection of ideas and possible variants of starting new ones”

Zenoviy Pavlyuk

Marketing Expert,
ÌÒS

The course, first of all, is interesting with interactive communication and discussion of the real cases. Consultant leads the topic of the discussion correcting all mistakes and suggests optimal decisions for presented situations”